Specialist - Customer Insights & Personalisation

MAIN OBJECTIVE OF ROLE To lead and translate complex customer data into actionable insights that drive improved customer experience, personalization, loyalty, and commercial performance. KEY RESPONSIBILITIES Analyses customer behavior across channels, segments, and lifecycle stages to uncover actionable insights– by conducting deep dives into customer journeys, identifying pain points, drop-offs, and growth opportunities. Designs and builds predictive models including churn prediction, propensity to buy or engage, next-best-action / next-best-offer frameworks, Customer Lifetime Value (CLV) models, and recommendation systems, while maintaining, monitoring, and optimizing model performance in production environments. Partners with Customer Relationship Management (CRM) and Digital teams to design and activate personalised campaigns and customer journeys, providing data-driven recommendations for offer optimization, targeting, and experimentation, while supporting the rollout of Customer Data Platform (CDP) and Advertising Technology (AdTech) capabilities with analytical logic. Designs A/B and multivariate tests to evaluate new experiences, features, and campaign initiatives. Collaborates closely with data engineering/IT teams to ensure robust pipelines, data integrity, and customer data unification. Develops customer segments using clustering, Recency-Frequency-Monetary (RFM), and behavioral analytics to support targeted engagement and personalization strategies. Builds dashboards, KPIs, and self-serve insight tools to enable business stakeholders to access and act on customer analytics. Translates complex analytical concepts into clear, compelling insights and narratives to support decision making. Ensures compliance with data privacy standards, including General Data Protection Regulation (GDPR) and internal governance policies. Conducts fairness and bias checks on datasets and predictive models to ensure accuracy, integrity, and unbiased outcomes. Builds frameworks to measure ROI, uplift, and attribution for marketing and product strategies and presents findings and strategic recommendations to stakeholders. Ensures customer data is accurate, reliable, and consistently unified. Partners with CX, Airport operations, Marketing, Digital, Product, CRM, and Data Engineering teams to align analytics initiatives with business priorities and ensure effective cross-functional delivery. QUALIFICATIONS Bachelor's Degree (3+ years) Fluent in English A minimum of 4 years of experience in data science or advanced analytics, ideally in customer-facing industries (retail, travel, e-commerce, telecom, loyalty, etc.). Strong proficiency in Python and SQL. Experience with data visualization (Tableau, or similar). Hands-on experience with cloud platforms (Azure, AWS, GCP) preferred. Strong knowledge of statistics, experiment design, and predictive modelling. Experience with machine learning frameworks (e.g., scikit-learn, XGBoost, TensorFlow/PyTorch a plus). Years with qualifications: 7 - 9 years COMPETENCIES Customer Focus Teamwork Effective Communication Personal Accountability & Commitment to achieve Resilience & Flexibility (Can do attitude) ISR REQUIREMENTS Reads and complies with the ISR policies of the Company and diligently reports any weakness or incidents to the respective Line Manager or the Information Security team. Completes all required ISR awareness sessions and follows associated guidelines in the day-to-day business operations.

Bachelor's Degree (3+ years) Fluent in English A minimum of 4 years of experience in data science or advanced analytics, ideally in customer-facing industries (retail, travel, e-commerce, telecom, loyalty, etc.). Strong proficiency in Python and SQL. Experience with data visualization (Tableau, or similar). Hands-on experience with cloud platforms (Azure, AWS, GCP) preferred. Strong knowledge of statistics, experiment design, and predictive modelling. Experience with machine learning frameworks (e.g., scikit-learn, XGBoost, TensorFlow/PyTorch a plus). Years with qualifications: 7 - 9 years

Analyses customer behavior across channels, segments, and lifecycle stages to uncover actionable insights– by conducting deep dives into customer journeys, identifying pain points, drop-offs, and growth opportunities. Designs and builds predictive models including churn prediction, propensity to buy or engage, next-best-action / next-best-offer frameworks, Customer Lifetime Value (CLV) models, and recommendation systems, while maintaining, monitoring, and optimizing model performance in production environments. Partners with Customer Relationship Management (CRM) and Digital teams to design and activate personalised campaigns and customer journeys, providing data-driven recommendations for offer optimization, targeting, and experimentation, while supporting the rollout of Customer Data Platform (CDP) and Advertising Technology (AdTech) capabilities with analytical logic. Designs A/B and multivariate tests to evaluate new experiences, features, and campaign initiatives. Collaborates closely with data engineering/IT teams to ensure robust pipelines, data integrity, and customer data unification. Develops customer segments using clustering, Recency-Frequency-Monetary (RFM), and behavioral analytics to support targeted engagement and personalization strategies. Builds dashboards, KPIs, and self-serve insight tools to enable business stakeholders to access and act on customer analytics. Translates complex analytical concepts into clear, compelling insights and narratives to support decision making. Ensures compliance with data privacy standards, including General Data Protection Regulation (GDPR) and internal governance policies. Conducts fairness and bias checks on datasets and predictive models to ensure accuracy, integrity, and unbiased outcomes. Builds frameworks to measure ROI, uplift, and attribution for marketing and product strategies and presents findings and strategic recommendations to stakeholders. Ensures customer data is accurate, reliable, and consistently unified. Partners with CX, Airport operations, Marketing, Digital, Product, CRM, and Data Engineering teams to align analytics initiatives with business priorities and ensure effective cross-functional delivery.